The DOI matches its Crossref record; 24 of the 24 references it cites were found in a registry or an index.
Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures
Abstract
Server consolidation based on virtualization is an important technique for improving power efficiency and resource utilization in cloud infrastructures. However, to ensure satisfactory performance on shared resources under changing application workloads, dynamic management of the resource pool via online adaptation is critical. The inherent tradeoffs between power and performance as well as between the cost of an adaptation and its benefits make such management challenging. In this paper, we present Mistral, a holistic controller framework that optimizes power consumption, performance benefits, and the transient costs incurred by various adaptations and the controller itself to maximize overall utility. Mistral can handle multiple distributed applications and large-scale infrastructures through a multi-level adaptation hierarchy and scalable optimization algorithm. We show that our approach outstrips other strategies that address the tradeoff between only two of the objectives (power, performance, and transient costs).
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Cites
Artificial intelligence: a modern approach
(1995) · Choice Reviews Online · doi:10.5860/choice.33-1577 · Cited by 21,974
Time Series Analysis: Forecasting and Control
Geurts, M., Box, G. E. P., & Jenkins, G. M. (1977) · Journal of Marketing Research · doi:10.2307/3150485 · Cited by 19,186
Artificial intelligence: A modern approach
Nilsson, N. J. (1996) · Artificial Intelligence · doi:10.1016/0004-3702(96)00007-0 · Cited by 10,583
Xen and the art of virtualization
Barham, P., Dragovic, B., Fraser, K., Hand, S., Harris, T., Ho, A., Neugebauer, R., Pratt, I., & Warfield, A. (2003) · ACM SIGOPS Operating Systems Review · doi:10.1145/1165389.945462 · Cited by 5,915
Time series analysis forecasting and control
Janacek, G. (2010) · Journal of Time Series Analysis · doi:10.1111/j.1467-9892.2009.00643.x · Cited by 2,584
Live migration of virtual machines
Clark, C. J., Fraser, K. A., Hand, S., Hansen, J. G., Jul, E., Limpach, C., Pratt, I., & Warfield, A. (2005) · doi:10.5555/1251203.1251223 · Cited by 2,562
Power provisioning for a warehouse-sized computer
Fan, X., Weber, W.-D., & Barroso, L. A. (2007) · Proceedings of the 34th annual international symposium on Computer architecture · doi:10.1145/1250662.1250665 · Cited by 1,797
Xen and the art of virtualization
Barham, P., Dragovic, B., Fraser, K., Hand, S., Harris, T., Ho, A., & Neugebauer, R. (2003) · Proceedings of the nineteenth ACM symposium on Operating systems principles - SOSP '03 · doi:10.1145/945461.945462 · Cited by 1,552
Managing energy and server resources in hosting centers
Chase, J. S., Anderson, D. C., Thakar, P. N., Vahdat, A. M., & Doyle, R. P. (2001) · Proceedings of the eighteenth ACM symposium on Operating systems principles · doi:10.1145/502034.502045 · Cited by 1,284
pMapper: Power and Migration Cost Aware Application Placement in Virtualized Systems
Verma, A., Ahuja, P., & Neogi, A. (2008) · Lecture Notes in Computer Science · doi:10.1007/978-3-540-89856-6_13 · Cited by 649
Cited by
Energy-aware Virtual Machine Migration for Cloud Computing - A Firefly Optimization Approach
Kansal, N. J., & Chana, I. (2016) · Journal of Grid Computing · doi:10.1007/s10723-016-9364-0 · Cited by 151
Network-Aware Virtual Machine Placement and Migration in Cloud Data Centers
Ferdaus, M. H., Murshed, M., Calheiros, R. N., & Buyya, R. (2015) · Advances in Systems Analysis, Software Engineering, and High Performance Computing · doi:10.4018/978-1-4666-8213-9.ch002 · Cited by 38
Swain, S. R., Parashar, A., Singh, A. K., & Lee, C. N. (2025) · The Journal of Supercomputing · doi:10.1007/s11227-024-06734-1 · Cited by 21
Metadata
- Authors
- Jung, G., Hiltunen, M. A., Joshi, K. R., Schlichting, R. D., & Pu, C.
- Venue
- 2010 IEEE 30th International Conference on Distributed Computing Systems
- Publisher
- IEEE
- Published
- 2010
- Pages
- 62-73
- OpenAlex
- W2128400269
- Cited by
- 299
- References
- 24
- FWCI
- 21.36
- Type
- conference paper
- Language
- en
- Open access
- closed
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- Jung, G., Hiltunen, M. A., Joshi, K. R., Schlichting, R. D., & Pu, C. (2010). Mistral: Dynamically Managing Power, Performance, and Adaptation Cost in Cloud Infrastructures. 2010 IEEE 30th International Conference on Distributed Computing Systems. https://doi.org/10.1109/icdcs.2010.88
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